A Web-Based Dynamic Nomogram to Calculate the Risk of Nonhealing after Femoral Neck Fracture Fixation among Young Adults: Bench to Bedside Translational Research
-
Babak Siavashi
,
Mohammad Heshmati
,
Mohammad Reza Golbakhsh
,
Seyyed Hossein Shafiei
,
Farhad Mahdavi
,
Mohammadreza Sadeghi
,
Yegane Yousefifar
,
Salar Baghbani
,
Mohammadreza Bozorgmanesh
Abstract
Background: The aim of this study was to develop a prognostic model to identify a subgroup of high-risk patients for non-healing after femoral neck fracture fixation among young adults. The model was implemented by presenting graphically as a nomogram that could be easily used in every day clinical cases.
Methods: Data on a total of 129 patients were included in the current study. The mean [standard deviation (SD)] age of the participants was 42 (13) years and 28% of the patients were women. Harrell’s C statistic was used as a measure of discrimination predictive power. We calculated the Nam-D’Agostino χ2 to examine calibration for prediction models.
Results: Approximately, 83% of fractures united uneventfully, with avascular necrosis (AVN), fixation nonhealing, non-union, infection, arthroplasty, and death being observed. Body mass index (BMI) and head acetabular trabecular angle (HATA) were inversely associated with the risk of all-cause nonhealing. The final model showed excellent discriminatory power [Harrell’s C statistic: 0.820, 95% confidence interval (CI) (0.680-0.960)] and it was well-calibrated [Nam-D’Agostino χ2: 10.1, (P = 0.3456)]. A
nomogram developed by incorporating significant predictors modelled without discretizing continuous variables.
Conclusion: Using readily available clinical and radiological data, we developed a parsimonious, simple, accurate yardstick to measure the 5-year risk of nonhealing after femoral neck fractures among young adults. In order to add ease-of-use and to promote its integration into clinical practice, the prognostic model was demonstrated visually as a statistic nomogram.
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22. Mohammadreza B, Farzad H, Davoud K, Fereidoun Prof AF. Prognostic significance of the complex "Visceral Adiposity Index" vs. simple anthropometric measures: Tehran lipid and glucose study. Cardiovasc Diabetol. 2012;11:20. doi: 10.1186/1475- 2840-11-20. [PubMed: 22394430]. [PubMed Central: PMC3376032].
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26. Barkhordari M, Padyab M, Sardarinia M, Hadaegh F, Azizi F, Bozorgmanesh M. Survival regression modeling strategies in CVD prediction. Int J Endocrinol Metab. 2016;14(2):e32156. doi: 10.5812/ijem.32156. [PubMed: 28058053]. [PubMed Central: PMC5192998].
27. D'agostino RB, Belanger A, D'agostino RB. A suggestion for using powerful and informative tests of normality. Am Stat. 1990;44(4):316-21. doi: 10.1080/00031305.1990.10475751.
28. D'Agostino RB, Nam BH. Evaluation of the performance of survival analysis models: Discrimination and calibration measures. Handbook of Statistics advances in survival analysis. 23th ed. Philadelphia, PA: Elsevier; 2003. p. 1-25
29. D'Agostino RB, Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: Results of a multiple ethnic groups investigation. JAMA. 2001;286(2): 180-7. doi: 10.1001/jama.286.2.180. [PubMed: 11448281].
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31. Hosmer DW, Lemeshow S, May S. Applied survival analysis: Regression modeling of time-to-event data. 2nd ed. Hoboken, NJ: Wiley-Interscience; 2008.
32. Demler OV, Paynter NP, Cook NR. Tests of calibration and goodness-of-fit in the survival setting. Stat Med. 2015;34(10):1659-80. doi: 10.1002/sim.6428. [PubMed: 25684707]. [PubMed Central: PMC4555993].
33. Hlatky MA. Exercise testing to predict outcome in patients with angina. J Gen Intern Med. 1999;14(1):63-5. doi: 10.1046/j.1525-1497.1999.00283.x. [PubMed: 9893094]. [PubMed Central: PMC1496444].
34. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007;115(7):928-35. doi: 10.1161/CIRCULATIONAHA.106.672402. [PubMed: 17309939].
35. Cook NR. Statistical evaluation of prognostic versus diagnostic models: Beyond the ROC curve. Clin Chem. 2008;54(1):17-23. doi: 10.1373/clinchem.2007.096529. [PubMed: 18024533].
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| Files | ||
| Issue | Vol 7, No 3 (2021) | |
| Section | Research Articles | |
| DOI | https://doi.org/10.18502/jost.v7i3.8104 | |
| Keywords | ||
| Femoral Neck Fracture; Nomograms; Risk | ||
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Siavashi B, Heshmati M, Golbakhsh MR, Shafiei SH, Mahdavi F, Sadeghi M, Yousefifar Y, Baghbani S, Bozorgmanesh M. A Web-Based Dynamic Nomogram to Calculate the Risk of Nonhealing after Femoral Neck Fracture Fixation among Young Adults: Bench to Bedside Translational Research. J Orthop Spine Trauma. 2022;7(3):85-94.
